• Design, develop and oversee the deployment of code in SQL, Python or other applicable languages to build client-facing analytical tools (REST APIs) and complex data pipelines. • Design and develop the orchestration of processes (via Airflow or native cloud tools) that ingest, join and process terabytes of both structured and unstructured data from multiple sources to distribute to storage repositories and API endpoints for data collaboration, AI and machine learning deployment initiatives. • Work with business leadership and technical teams to gather requirements and ensure development work meets business needs; communicate architectural designs to leadership to ensure scope is appropriately captured. • Establish design standards for the development of data pipelines and engineering tools that leverage AI/ML; ensure code is consistent and repeatable. • Provide mentorship to junior team members by assisting with the scoping and architecture of projects from a technical lens. • Provide expertise in development and architecture best-practices within SQL, Python, Airflow and cloud environments such as Google Cloud, Snowflake and AWS.

This description is a summary of our understanding of the job description. Click on 'Apply' button to find out more. Role Description The Principal, Head of Data & AI Transformation Programs will lead the orchestration of EDB’s enterprise-wide AI initiatives. This leader will connect strategy with execution, driving adoption, governance, and delivery of AI and data initiatives across the organization. - Lead and manage the execution of EDB’s strategic Data, Automation, and AI roadmap from concept through production deployment. - Translate high-level AI strategy into actionable, measurable programs with clear technical milestones and KPIs. - Partner with Engineering and IT to ensure the scalable, secure, and compliant delivery of AI initiatives across EDB. - Drive productionization of AI workflows, shifting from business-led proofs of concept to centrally supported, operationalized systems. - Define and evolve the operating model for AI deployment, integrating data engineering, MLOps, and governance frameworks. - Act as an AI enablement leader by embedding AI capabilities into core workflows across business functions. - Partner with HR and Communications to scale digital fluency and AI literacy initiatives company-wide. - Build repeatable enablement frameworks for internal and customer-facing AI applications within the Customer Zero model. - Lead continuous feedback loops between internal users, product, and data teams to inform future enhancements. - Collaborate with Product, Engineering, Legal, and Security teams to implement AI governance and data management standards. - Partner with Trust, Risk, and Compliance to ensure all AI workloads adhere to security and regulatory policies. - Drive alignment with the Central AI Committee and Communities of Practice on tooling, data access, and AI deployment patterns. - Support EDB’s Postgres AI and Sovereign AI roadmaps, ensuring integration across analytical, transactional, and ML systems. - Define, track, and report on KPIs tied to AI-driven business value such as automation efficiency, customer engagement, and retention uplift. - Partner with BI teams to operationalize these metrics within tools like Tableau or other observability platforms. - Build and maintain visibility into AI workloads, resource utilization, and infrastructure cost forecasting. - Lead the measurement and reporting of impact across all AI initiatives, from internal productivity gains to customer outcomes. Qualifications - 10+ years leading Data, AI, or Digital Transformation initiatives, ideally in enterprise environments. - Proven experience building and managing data-centric or AI programs that bridge business, technical, and governance domains. - Strong understanding of AI systems and architecture, including embedded AI, generative AI, BYOAI, and model deployment frameworks. - Experience with data governance, MLOps, and automation tools, along with familiarity with cloud environments such as AWS, GCP, or Azure. - Strong program management skills, comfortable driving complex, multi-stakeholder initiatives from inception to delivery. - Ability to translate complex technical concepts into actionable strategies and execution plans. - Strong collaboration and communication skills, with experience engaging senior leadership and cross-functional teams. Requirements - Experience working in a “Customer Zero” or similar internal piloting and development capacity. - Familiarity with challenges related to data fragmentation and the need for centralized, structured data. - Experience in change management for new technology adoption, including addressing adoption concerns across teams. Benefits - Access to CuraLinc to aid employees in health and wellness tips and practices. - Wellness Fridays extending to December 2026. Company Description EDB provides a data and AI platform that enables organizations to harness the full power of Postgres for transactional, analytical, and AI workloads across any cloud, anywhere. EDB empowers enterprises to control risk, manage costs and scale efficiently for a data and AI led world. - Serving more than 1,500 customers globally. - Leading contributor to the vibrant and fast-growing PostgreSQL community. - Supports major government organizations, financial services, media and information technology companies. - Delivers the confidence of up to 99.999% high availability with mission critical capabilities built in such as security, compliance controls, and observability.

• Translate Kognia’s data into recruitment and tactical frameworks • Build role-based and position-specific player benchmarks • Create comparative league models to support cross-league recruitment • Structure data warehouse views that support deep-dive analysis • Ensure insights are usable inside real club workflows • Collaborate Across the Business to improve data usability • Support commercial conversations where technical validation is required • Stay up to date with the latest trends in football data analytics and technology

• Lead the evaluation and continuous improvement of entity resolution and entity linking pipelines. • Debug new builds, identify anomalies, and recommend modeling or system-level improvements. • Define, implement, and maintain scalable performance and quality metrics, leveraging automation and LLM-based approaches where appropriate. • Partner with Engineering to optimize entity linking and ranking systems using Learning-to-Rank and related techniques. • Design methods to assess and classify entity confidence and quality across the graph. • Design and implement a comprehensive data quality framework for graph-based identity data. • Translate abstract quality concepts (e.g., reliability, stability, consistency) into measurable signals. • Use data quality insights to guide modeling decisions, experimentation strategy, and product prioritization. • Identify and operationalize generalized, high-impact predictive signals derived from graph structure, temporal dynamics, and relational patterns. • Develop scalable approaches to link prediction, label propagation, and semi-supervised learning within the ID Graph. • Explore and evaluate advanced graph modeling techniques, including graph-based ML, knowledge graph methods, and Graph Neural Networks (GNNs), when appropriate. • Focus on durable abstractions rather than one-off features, ensuring solutions are explainable, compliant, and reusable across multiple products. • Collaborate closely with Engineering, Product Management, Compliance, and downstream product teams. • Act as a technical leader within the Identity organization, influencing modeling standards, experimentation rigor, and best practices. • Translate complex technical findings into clear insights and recommendations for both technical and non-technical stakeholders. • Support the launch of new product capabilities built on top of the ID Graph. • Demonstrate strong ownership, strategic impact, and assertive communication. • Mentor peers, foster a culture of growth, and build authentic relationships across teams. • Embrace feedback, adapt resiliently to challenges, and pursue continual self-improvement.